Intelligent service method, device, equipment, medium and product

Abstract

The invention discloses an intelligent service method, device and equipment, a medium and a product, relates to the technical field of large-model intelligent services, and can be applied to the field of financial science and technology. Obtaining a target task in response to a user input operation of the interactive interface; performing thinking chain enhancement on the target task through a thinking chain management platform to obtain a target thinking chain; and calling at least one target model and a target service based on the target thinking chain to process the target task. By adopting the technical scheme, the problem of how to enhance the service capability of a large model in a complex scene is solved; by constructing the thinking chain management platform to perform thinking chain enhancement on the target task, it is ensured that the service capability of a large model can be enhanced in a complex scene, and the user experience is improved.

Description

Technical Field

[0001] This invention relates to the field of large-scale intelligent service technology, and can be applied to the field of financial technology. In particular, it relates to an intelligent service method, device, equipment, medium and product. Background Technology

[0002] Current large-scale model service capabilities rely on training data, model architecture, fine-tuning strategies, and prompt word engineering methods. By organizing the solution steps through a thought process, intelligent service for tasks can be achieved.

[0003] However, prompt word engineering methods, which provide prompt words similar to expert templates by organizing them by domain, can improve the user experience to some extent; model instruction fine-tuning methods, which fine-tune the instruction set of a large model based on domain data, have high training costs and are prone to producing poor results; agent-related methods, which use contextual memory, task planning, and tool usage to handle complex problems; the above-mentioned existing methods often have high training costs and generally perform poorly in complex scenarios, and there is still no mature solution.

[0004] Therefore, there is an urgent need for an intelligent service approach that can enhance the service capabilities of large models in order to handle problems in complex scenarios. Summary of the Invention

[0005] This invention provides an intelligent service method, apparatus, device, medium, and product that solves the problem of how to enhance the service capabilities of large models in complex scenarios. By constructing a thought chain management platform to enhance the thought chain of target tasks, it ensures that the service capabilities of large models can be enhanced in complex scenarios, thereby improving the user experience.

[0006] According to one aspect of the present invention, an intelligent service method is provided, comprising:

[0007] Responding to user input on the interactive interface, retrieve the target task;

[0008] The target task is enhanced by using a mind chain management platform to obtain the target mind chain.

[0009] Based on the target thinking chain, at least one target model and target service are invoked to process the target task.

[0010] According to another aspect of the present invention, an intelligent service device is provided, comprising:

[0011] The acquisition module is used to acquire the target task in response to user input operations on the interactive interface;

[0012] The target thinking chain determination module is used to enhance the thinking chain of the target task through the thinking chain management platform to obtain the target thinking chain.

[0013] The processing module is used to process the target task by invoking at least one target model and target service based on the target thought chain.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the intelligent service method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the intelligent service method described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the intelligent service method according to any embodiment of the present invention.

[0020] The technical solution of this invention addresses how to enhance the service capabilities of large models in complex scenarios by constructing a mind chain management platform to enhance the mind chain of target tasks; it ensures the enhancement of the intelligent service capabilities of large models in complex scenarios and improves user experience.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of an intelligent service method provided according to an embodiment of the present invention;

[0024] Figure 2This is a flowchart of a method for obtaining a target thought chain according to an embodiment of the present invention;

[0025] Figure 3 This is a flowchart of an intelligent service method provided according to an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of the structure of an intelligent service device according to an embodiment of the present invention;

[0027] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the intelligent service method of the present invention. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product or device.

[0030] Furthermore, it should be noted that the information collected in the technical solution of this invention is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of related data all comply with the relevant laws, regulations and standards of relevant countries and regions, necessary confidentiality measures have been taken, and public order and good morals are not violated. Corresponding operation entry points are provided for users to choose to authorize or refuse.

[0031] Figure 1 This invention provides a flowchart of an intelligent service method, applicable to situations where business needs are intelligently analyzed based on a large model service in complex scenarios. This method can be executed by an intelligent service device, which can be implemented in hardware and / or software and configured within a server. Figure 1 As shown, the method includes:

[0032] S110: Respond to user input on the interactive interface and obtain the target task.

[0033] The interactive interface is the interface for implementing intelligent services, which can be a visual interface that encapsulates the mind chain management platform through a plugin; the input operation can be the user's current service request; and the target task is the task information obtained by summarizing the user's service request.

[0034] Specifically, in response to user input on the visual interface provided by the plugin that encapsulates the MindChain management platform, the target task corresponding to the user's current needs is obtained.

[0035] In one optional embodiment of the present invention, the intelligent service is initiated in response to the user's submission operation; this includes: after obtaining the target task, providing pre-recommendation of prompt words based on the target task, and in response to the user's confirmation operation, obtaining the prompt words confirmed by the user for the target task; by providing pre-recommendation and selection of prompt words, the accuracy of subsequent thought chain enhancement is ensured, the efficiency of thought chain matching is improved, thereby improving the efficiency of the intelligent service and enhancing the user experience.

[0036] Optionally, in response to user input on the interactive interface, the target task is retrieved, including:

[0037] Event tracking is performed based on tracking strategies;

[0038] Responding to user input on the interactive interface, triggering the execution logic;

[0039] Obtain the target task by tracking events.

[0040] The data tracking strategy includes the location and number of data tracking points; the data tracking point location can be an extended function, such as menu items, toolbar buttons, shortcut keys, etc.; the trigger mechanism can be a user input operation to complete the operation, or a query confirmation operation in the interactive interface; the execution logic is to obtain the target task.

[0041] Specifically, based on existing tracking strategies, extended functionality tracking can be implemented through extended tracking points, such as menu items, toolbar buttons, and shortcut keys. Event tracking can capture defined actions in a timely manner, obtain user input operations in the interactive interface, and trigger execution logic if the input operation is an input completion operation or a query confirmation operation in the interactive interface. Event tracking can be used to obtain the target task of this user input.

[0042] Understandably, the interactive interface displayed by the built plugin enables interaction with the user, timely capture of user actions, accurate acquisition of target tasks, and real-time processing of target tasks through the encapsulated plugin, thereby improving the intelligent service capabilities of large models in complex scenarios.

[0043] S120. Enhance the target task's mind chain through the mind chain management platform to obtain the target mind chain.

[0044] The mind chain management platform is pre-built and includes at least one mind chain; each mind chain is marked with its domain and prompt words; the target mind chain is the mind chain corresponding to the target task, that is, the steps to solve the task.

[0045] Specifically, the target task is matched with a pre-built mind chain management platform to find the mind chain that matches the target task as the target mind chain.

[0046] Optional, such as Figure 2 The method shown involves obtaining a target mind chain by enhancing the mind chain of the target task through a mind chain management platform, resulting in the target mind chain, including:

[0047] S121. Perform semantic analysis on the target task to obtain the task requirements and task domain.

[0048] Semantic analysis can be performed using a language processing model; task requirements are the extracted task objectives. For example, if the target task is "I want to know the automatic assembly principle of a certain module in the R&D field", then the corresponding task requirements can be "a certain module" and "automatic assembly principle"; the task domain is the domain to which the target task belongs, which can include software development, knowledge question answering, etc.

[0049] Specifically, semantic analysis of the target task can be performed using a language processing model, and the task requirements and domain of the target task can be obtained based on the semantic analysis results.

[0050] S122. Recommend prompt words for task requirements and obtain at least one target prompt word.

[0051] Among them, the prompt words are keywords summarized based on task requirements; the target prompt words are prompt words determined based on the user's input operations.

[0052] Specifically, after obtaining the target task based on the interactive interface displayed by the plugin, at least one prompt word is output to the user directly based on the task requirements obtained from the analysis of the target task, providing key point prompts, and the target prompt word determined by the user is obtained based on the user's input operation; the target prompt word is the key point of the user's subjective needs.

[0053] Understandably, recommending prompts through an interactive interface and obtaining user confirmation of those prompts further ensures the subjectivity of subsequent thought chain enhancement, avoiding semantic misunderstandings that could lead to incorrect handling of intelligent services. This provides a subjective basis for the accuracy of intelligent services, thereby further improving their efficiency and accuracy.

[0054] In one optional embodiment of the present invention, if the displayed suggested words are unreasonable, the user can click the "Continue Search" button to receive further suggested words so that the user can determine the target suggested word; by providing secondary suggestions, the accuracy of the thought chain determination is enhanced, further realizing the user's personalized experience and intelligent service.

[0055] S123. Obtain at least one candidate thought chain from the thought chain management platform based on the task domain.

[0056] Among them, candidate thought chains are thought chains under each task domain in the thought chain management platform.

[0057] Specifically, based on the task domain to which the target task belongs, all candidate thought chains under that task domain are obtained from the thought chain management platform.

[0058] S124. Match the target prompts and candidate thought chains to obtain the target thought chain.

[0059] Each candidate thought chain is marked with a corresponding prompt word.

[0060] Specifically, the system matches the target prompt words selected by the user with the prompt words marked on the candidate thought chains, and uses the successfully matched candidate thought chains as the target thought chains.

[0061] Understandably, by performing semantic analysis on the target task and confirming the user's personalized needs, the accuracy of the thought chain acquisition can be enhanced, thereby improving the effectiveness of subsequent intelligent services and ensuring the accuracy of intelligent services in complex scenarios based on the user's personalized needs.

[0062] S130. Based on the target thinking chain, call at least one target model and target service to process the target task.

[0063] Among them, the target model is the processing model required to solve each function in the thinking chain steps, which can be a large model; the target service is the service exposed by the platform, such as SMS service, weather service, and billing service.

[0064] Specifically, based on the acquired target thinking chain, the corresponding target models and platform-exposed target services are sequentially invoked to process the target task.

[0065] Optionally, based on the target thinking chain, at least one target model and target service are invoked to process the target task, including:

[0066] At least one target model is invoked sequentially according to the target thinking chain;

[0067] Based on the task domain to which the target thinking chain belongs, the target service is called from the service whitelist of the service platform through the service interface; the service whitelist is determined based on user permissions.

[0068] The target task is processed based on the target model and target service, and the results are fed back in a workflow manner.

[0069] The target model can be a large model, such as an artificial intelligence model; the service whitelist refers to the services exposed by the service platform, which are pre-determined based on the user's permissions.

[0070] Specifically, at least one target model is called sequentially according to the target thinking chain; and based on the task domain to which the target thinking chain belongs, the corresponding target service is called from the service whitelist determined based on user permissions according to the service interface; the target task is processed according to the called target model and target service, and the service result is obtained by processing in a workflow manner, and the service result is displayed through the interactive interface.

[0071] Understandably, while providing intelligent services for tasks through artificial intelligence models, in order to further solve specific problems in multiple scenarios and fields, platform services from the service whitelist determined by user permissions are called according to the relevant field, such as SMS service, weather service, and billing service; calling different services according to the thought chain can effectively solve complex problems and improve the practicality of intelligent services.

[0072] This invention, in its embodiments, obtains a target task by responding to user input on an interactive interface; enhances the target task's thought chain through a thought chain management platform to obtain a target thought chain; and processes the target task by invoking at least one target model and target service based on the target thought chain. This technical solution addresses how to enhance the service capabilities of large models in complex scenarios; by constructing a thought chain management platform to enhance the target task's thought chain, it ensures that the service capabilities of large models can be enhanced in complex scenarios, further improving the user experience.

[0073] Figure 3 This is a flowchart illustrating an intelligent service method provided by an embodiment of the present invention. Based on the above embodiments, this embodiment supplements the construction method of the mind chain management platform. It should be noted that for parts not detailed in this embodiment, please refer to the relevant descriptions in other embodiments, such as... Figure 3 As shown, the method includes:

[0074] S210. Obtain historical tasks; historical tasks include historical domains and historical thought chains.

[0075] Among them, historical tasks are tasks that provide intelligent services for history.

[0076] Specifically, the tasks of acquiring historical data for intelligent services, and the corresponding historical domains and historical thought chains.

[0077] S220. Based on the historical domain, the historical tasks are divided to obtain at least one task group; the task group includes at least one historical thought chain.

[0078] Specifically, historical tasks are divided into domains based on the historical field to which each historical task belongs. Each task group includes at least one historical task, and each historical task carries a corresponding historical thought chain.

[0079] It is understandable that historical tasks are divided into domains to facilitate the pre-allocation of thought chains for subsequent determination, reduce the workload and data volume of thought chain matching, further organize the steps for solving target tasks by domain, and improve the intelligent service capabilities in complex scenarios.

[0080] S230. Semantic processing of the historical thought chain yields historical prompt words.

[0081] Specifically, semantic processing is performed on the historical thought chain corresponding to each historical task to obtain the key points corresponding to that historical task as historical prompt words.

[0082] Understandably, by acquiring key points from historical thought chains, the matching efficiency of thought chains can be ensured, thereby further improving the efficiency of intelligent services.

[0083] S240. Link historical domains, historical keywords, and historical thought chains to build a thought chain management platform.

[0084] Specifically, based on the historical domain, at least one historical task is identified, each historical task is converted into a corresponding historical thought chain, and the historical thought chains are marked based on historical prompts. Thus, each historical domain has at least one historical thought chain, and each historical thought chain carries a corresponding historical prompt. Each historical thought chain is then constructed into a thought chain management platform.

[0085] Optionally, after building the mind chain management platform, it may also include:

[0086] Obtain user input through the interactive interface;

[0087] The task domain is determined based on the input operation; the task domain is the research and development domain.

[0088] Obtain at least one research problem in the research and development field, and the corresponding research and development thought chain for the research problem;

[0089] The research and development issues are linked to the research and development thought chain and stored in the thought chain management platform.

[0090] Among them, input operations can be customized operations of the user on the thought chain; R&D field can be the entire R&D life cycle; R&D problems are the problems existing in the current R&D life cycle, such as requirements analysis, requirements design, code development, code testing, system operation and maintenance, etc.; R&D thought chain is the solution approach corresponding to each R&D problem; for example, requirements analysis R&D problems, describing common problems such as designing an order system that supports high concurrency, and the solution approach.

[0091] Specifically, the system obtains user customization operations for the thought chain through the interactive interface, and obtains the set R&D domain, i.e., the R&D life cycle, based on the input operations; it further sorts out at least one R&D problem in the R&D domain, such as requirements analysis, requirements design, code development, code testing, system operation and maintenance, and the corresponding R&D thought chain for the R&D problem; it then associates the R&D problem with the corresponding R&D thought chain and maintains it in the thought chain management platform.

[0092] Understandably, by identifying problems throughout the entire R&D lifecycle, intelligent demand analysis and functional design generation can be achieved, thereby improving R&D efficiency.

[0093] In one optional embodiment of the present invention, the mind chain can also be automatically or manually maintained on the interactive interface of the mind chain management platform. The domain problem and mind chain can be obtained first through a large model, and then fed back to professionals through the interactive interface for modification. This ensures that the management platform interface automatically uploads relevant data, thereby realizing the automated operation and maintenance of the mind chain platform.

[0094] S250: Responds to user input on the interactive interface and obtains the target task.

[0095] S260. Enhance the target task's mind chain through the mind chain management platform to obtain the target mind chain.

[0096] S270. Based on the target thinking chain, call at least one target model and target service to process the target task.

[0097] This invention, through the construction of a thinking chain management platform, automates data collection and organization into thinking chains. It also allows for the customization and maintenance of thinking chains via an interactive interface. The platform organizes problem-solving steps by domain and maintains them, providing suggested keywords and thinking chains formed by multiple key steps to assist in model reasoning for subsequent intelligent services. This ensures efficiency in solving complex problems and improves the accuracy and practicality of large-scale intelligent services.

[0098] Figure 4 This is a schematic diagram of an intelligent service device provided in an embodiment of the present invention. This embodiment of the present invention is applicable to situations where business requirements are intelligently analyzed based on large-model services. The intelligent service device can be implemented in hardware and / or software and can be configured in a server. Figure 4 As shown, the intelligent service device 300 includes an acquisition module 310, a target thought chain determination module 320, and a processing module 330:

[0099] The acquisition module 310 is used to acquire the target task in response to user input operations on the interactive interface;

[0100] The target thinking chain determination module 320 is used to enhance the thinking chain of the target task through the thinking chain management platform to obtain the target thinking chain.

[0101] Processing module 330 is used to process target tasks by calling at least one target model and target service based on the target thinking chain.

[0102] This invention, in its embodiments, obtains a target task by responding to user input on an interactive interface; enhances the target task's thought chain through a thought chain management platform to obtain a target thought chain; and processes the target task by invoking at least one target model and target service based on the target thought chain. This technical solution addresses how to enhance the service capabilities of large models in complex scenarios; by constructing a thought chain management platform to enhance the target task's thought chain, it ensures that the service capabilities of large models can be enhanced in complex scenarios, further improving the user experience.

[0103] Optionally, the target thinking chain determination module 320 is used to perform semantic analysis on the target task to obtain task requirements and task domain;

[0104] Recommend prompts for task requirements to obtain at least one target prompt;

[0105] Obtain at least one candidate mind chain from the mind chain management platform based on the task domain;

[0106] The target thought chain is obtained by matching the target cue words with the candidate thought chains.

[0107] Optionally, the intelligent service device 300 also includes a mind chain management platform building module for...

[0108] Acquire historical tasks; historical tasks include historical domains and historical thought chains;

[0109] Based on the historical domain, historical tasks are divided into at least one task group; each task group includes at least one historical thought chain.

[0110] Semantic processing of historical thought chains yields historical cue words;

[0111] By linking historical domains, historical keywords, and historical thought chains, a thought chain management platform can be built.

[0112] Optionally, the MindChain management platform building module is also used to obtain user input operations through the interactive interface;

[0113] The task domain is determined based on the input operation; the task domain is the research and development domain.

[0114] Obtain at least one research problem in the research and development field, and the corresponding research and development thought chain for the research problem;

[0115] The research and development issues are linked to the research and development thought chain and stored in the thought chain management platform.

[0116] Optionally, the acquisition module 310 is also used for event tracking based on the tracking strategy;

[0117] Responding to user input on the interactive interface, triggering the execution logic;

[0118] Obtain the target task by tracking events.

[0119] Optionally, the processing module 330 is also used to sequentially call at least one target model according to the target thinking chain;

[0120] Based on the task domain to which the target thinking chain belongs, the target service is called from the service whitelist of the service platform through the service interface; the service whitelist is determined based on user permissions.

[0121] The target task is processed based on the target model and target service, and the results are fed back in a workflow manner.

[0122] The intelligent service device provided in the embodiments of the present invention can execute the intelligent service method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0123] According to embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0124] Figure 5A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0125] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0126] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0127] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as intelligent service methods.

[0128] In some embodiments, the smart service method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the smart service method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the smart service method by any other suitable means (e.g., by means of firmware).

[0129] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0130] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0131] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0132] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0133] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0134] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product within the cloud computing service system. This addresses the shortcomings of traditional physical hosts and dedicated virtual services, such as high management difficulty and weak business scalability.

[0135] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0136] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An intelligent service method, characterized in that, include: Responding to user input on the interactive interface, retrieve the target task; The target task is enhanced by using a mind chain management platform to obtain the target mind chain. Based on the target thinking chain, at least one target model and target service are invoked to process the target task.

2. The method according to claim 1, characterized in that, The step of enhancing the target task's thought chain through the thought chain management platform to obtain the target thought chain includes: Semantic analysis is performed on the target task to obtain the task requirements and task domain; Based on the task requirements, prompt words are recommended to obtain at least one target prompt word; At least one candidate thought chain is obtained from the thought chain management platform based on the task domain; The target thought chain is obtained by matching the target prompt words with the candidate thought chains.

3. The method according to claim 1 or 2, characterized in that, The mind chain management platform is constructed in the following way: Acquire historical tasks; these historical tasks include historical domains and historical thought chains. Based on the historical domain, the historical tasks are divided into at least one task group; the task group includes at least one historical thought chain; Semantic processing of the historical thought chain yields historical prompt words; By associating the historical domain, the historical prompts, and the historical thought chain, a thought chain management platform is constructed.

4. The method according to claim 3, characterized in that, After building the mind chain management platform, it also includes: Obtain user input through the interactive interface; The defined task domain is obtained based on the input operation; the task domain is a research and development domain. Obtain at least one research problem in the research field and the corresponding research thought chain for the research problem; The research and development problem and the research and development thought chain are associated and stored in the thought chain management platform.

5. The method according to claim 1, characterized in that, The process of obtaining the target task in response to user input on the interactive interface includes: Event tracking is performed based on tracking strategies; Responding to user input on the interactive interface, triggering the execution logic; The target task is obtained through the event tracking points.

6. The method according to claim 1, characterized in that, The process of invoking at least one target model and target service to process the target task based on the target thinking chain includes: At least one target model is invoked sequentially according to the target thinking chain; Based on the task domain to which the target thinking chain belongs, the target service is invoked from the service whitelist of the service platform through the service interface; the service whitelist is determined based on user permissions. The target task is processed based on the target model and the target service, and the results are fed back in a workflow manner.

7. An intelligent service device, characterized in that, include: The acquisition module is used to acquire the target task in response to user input operations on the interactive interface; The target thinking chain determination module is used to enhance the thinking chain of the target task through the thinking chain management platform to obtain the target thinking chain. The processing module is used to process the target task by invoking at least one target model and target service based on the target thought chain.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the intelligent service method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the intelligent service method according to any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the intelligent service method according to any one of claims 1-6.

Images